CHORALized events

The bond between Physics and Artificial Intelligence has never been stronger, as underscored by last year's Nobel Prize, awarded to Hinton and Hopfield, whose discoveries were central topics throughout the conference.

Only a few months have passed since our first edition, yet this short time has been enough for major developments to emerge, drastically reshaping our world from political, social, and scientific perspectives.

This rapid progress demands that the scientific community work to explain a wide range of phenomena that lie at the heart of AI’s functioning but remain largely understood only at an empirical level. Despite this, AI's success is so remarkable that it is now embedded in numerous devices, many of which are used daily by most of us. Addressing fundamental theoretical questions and achieving a deeper understanding of the basic building blocks of machine learning models and training algorithms remains crucial.

Given the high-dimensional nature of real-world data and the vast number of tunable parameters in machine learning models, statistical physics and high-dimensional inference provide a natural framework. Since Gardner and Derrida’s seminal works on the perceptron in the 1980s, the interplay between disciplines has led to a wealth of innovative ideas and insights into the functioning of neural networks.

This multidisciplinary conference aims to bring together researchers from statistical physics, mathematical physics, and machine learning. Our goal is to provide diverse perspectives on key topics in contemporary machine learning, including: Associative memories, diffusion models, energy-based models, representation learning and structured data modeling, language modeling, self-supervised learning, reasoning, and alternative learning paradigms, mathematical physics approaches to high-dimensional probability, spin glasses, and Boltzmann machines, theoretical aspects of neural networks.

Dates: 3-10 July, 2025

Location: International Center for Theoretical Physics, Trieste, Italy.

Website: https://indico.ictp.it/event/10849

The sixth edition of "Youth in High Dimensions" will give to young researchers the opportunity to present recent results on statistical problems, in areas ranging from machine learning and inference to neuroscience or statistical physics. Typical problems in high-dimensions include estimating noisy signals (compressed sensing, PCA and tensor decomposition), analysing (deep) neural networks, detecting communities in large networks, or modelling disordered spin systems. These seemingly unrelated problems share many similarities in their phenomenology and in the tools used to analyse them. The core of the field is made of a very active, diverse and quickly expanding community of physicists, computer scientists, mathematicians, information theorists and engineers, with the common desire to tackle increasingly challenging problems at the forefront of data science.